Eigenvalue — where it appears
Named by 2 essays across 2 fields — each of them below, with the objects they name alongside it.
A matrix that depends on its own eigenvalue
A damped structure does not produce Ax = λx. It produces (λ²M + λC + K)x = 0, where the matrix whose null vector is wanted is a function of the number being solved for — so there is nothing to factorise, an n × n problem has 2n answers, and the eigenvectors cannot be a basis.
Where the drift lands
The standing rule for when a preconditioner has gone stale is to rebuild it once the matrix has changed by more than some fraction of itself. Two drifts of exactly the same relative size cost 19 iterations and 5 on the same matrix, and the quantity that separates them is not in the rule at all — the perturbation is divided by the eigenvalue it lands on.
Named alongside it
The objects these essays reach for when they reach for this one.
AnisotropyCholesky factorisationCompanion formCondition numberConjugate gradientsEigenvalue at infinityExact ground truthFlop countIncomplete factorisationLinearisationMatrix polynomialPreconditioning